Summary: Seeking a Lead Generative AI Operations Engineer to architect and sustain robust ML infrastructure, developing scalable MLOps pipelines to transition AI projects to production. Highlights: 1. Architect and sustain robust ML infrastructure for seamless AI deployment 2. Develop scalable MLOps pipelines from prototype to production 3. Make a significant impact on AI services within the IT Chief Data Office We are seeking a **Lead Generative AI Operations Engineer** to architect and sustain a robust ML infrastructure that supports seamless AI deployment. In this role, you will work cross\-functionally to develop scalable MLOps pipelines and infrastructure, enabling data scientists and engineers to transition ML projects from prototype stages to production environments. Join us to make a significant impact on AI services within the IT Chief Data Office. **Responsibilities** * Design scalable AI and machine learning workloads that align with company objectives * Develop and uphold reproducible machine learning pipelines * Deploy AI models into production using model serving infrastructures * Implement monitoring and logging frameworks for AI service observability * Define infrastructure needs for MLOps pipelines and related components * Collaborate with infrastructure engineers to facilitate infrastructure deployment * Guide and mentor team members to encourage best practices and ongoing improvement * Coordinate efforts with cross\-functional teams including data scientists and engineers * Optimize machine learning workloads for enhanced performance and scalability * Ensure adherence to security protocols and data privacy regulations * Assess new tools and technologies to improve AI service delivery * Document system designs and workflows for knowledge dissemination * Diagnose and resolve production issues affecting AI services **Requirements** * Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related discipline * Over 5 years of experience in AI, machine learning, data engineering, software development, or cloud infrastructure * Strong expertise in Python and proficiency with AI/ML frameworks such as PyTorch, TensorFlow, HuggingFace, or Scikit\-learn * Experience with model inference runtimes including vLLM, MLServe, or Torch Serve * Proficiency in containerization and orchestration technologies such as Docker and Kubernetes * Experience specifying and implementing infrastructure requirements for ML pipelines * Strong analytical and problem\-solving capabilities with experience in agile cross\-disciplinary teams * Effective communication and mentoring abilities to support team growth * English language proficiency at B2 level or higher **Nice to have** * Familiarity with cloud platforms like Azure, AWS, or Google Cloud * Understanding of Infrastructure as Code (IaC) methodologies * Experience with experiment tracking systems and pipeline orchestration tools